0da218a8-2882-4ee7-bb2a-50a51f7f4138 English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2025-11-13T16:15:02 UK GEMINI 2.3 WGS 84 / Pseudo-Mercator Functional traits of woody plants sampled in permanent forest monitoring plots along altitudinal and forest perturbation gradients in the Colombian Andes, 2019-2022 2023-09-12 publication https://catalogue.ceh.ac.uk/id/0da218a8-2882-4ee7-bb2a-50a51f7f4138 10.5285/0da218a8-2882-4ee7-bb2a-50a51f7f4138 doi: Salgado-Negret, B., Hernández-Torres, L.H., Serrano, J., López, L.G., Pennington, T., Feldpausch, T.R. (2023). Functional traits of woody plants sampled in permanent forest monitoring plots along altitudinal and forest perturbation gradients in the Colombian Andes, 2019-2022. NERC EDS Environmental Information Data Centre 10.5285/0da218a8-2882-4ee7-bb2a-50a51f7f4138 The dataset contains information on six functional traits of woody plants, including Leaf Area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC), Leaf Thickness (Lth), Wood Density (WD), Bark Thickness (BT). It also includes data on concentrations of C, N, P, Ca, Mg, and K in leaves; leaf fresh mass and leaf dry mass data; and fresh wood volume and dry wood mass data to calculate Wood Density. Ten leaves per individual were sampled, and three measurements were taken for leaf thickness at the base, middle, and top of the leaf. For wood density, a single branch sample was taken per individual and for bark thickness five measurements per individual were made. The data were collected between 2019 and 2022 from 27 forest monitoring plots (0.5 ha each) in five locations along an altitudinal (lowland, mid-elevation, and highland forests) and forest perturbation (low, medium, and high perturbation levels) gradient in Andean ecosystems in Colombia. The database includes information about the plot location and parameters of the locality. The purpose of this data collection was to determine whether the expression of functional traits in woody plants differs between the perturbation gradient and the relationship of the traits to ecosystem processes. This information is important for understanding the drivers of variation in forest resilience and the impacts of perturbation on ecosystem functioning. This data set was obtained within the framework of the BioResilience project, a transdisciplinary investigation that seeks to understand the resilience of forest ecosystems after the post-conflict period in Colombia. Full details about this dataset can be found at https://doi.org/10.5285/0da218a8-2882-4ee7-bb2a-50a51f7f4138 Salgado-Negret, B. Universidad Nacional de Colombia bsalgadon@unal.edu.co https://orcid.org/0000-0002-3103-9878 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Hernández-Torres, L.H. Universidad Nacional de Colombia lhhernandezt@unal.edu.co https://orcid.org/0009-0009-3753-6304 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Serrano, J. Fauna and Flora International juliserranoa@yahoo.com https://orcid.org/0000-0002-9751-5339 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author López, L.G. University of Tolima lglopez@ut.edu.co https://orcid.org/0000-0002-3851-0714 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Pennington, T. University of Exeter T.Pennington@exeter.ac.uk https://orcid.org/0000-0002-8196-288X ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Feldpausch, T.R. University of Exeter T.R.Feldpausch@exeter.ac.uk https://orcid.org/0000-0002-6631-7962 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Feldpausch, T.R. University of Exeter t.r.feldpausch@exeter.ac.uk https://orcid.org/0000-0002-6631-7962 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information pointOfContact Salgado-Negret, B. Universidad Nacional de Colombia bsalgadon@unal.edu.co https://orcid.org/0000-0002-3103-9878 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information pointOfContact NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC EDS Environmental Information Data Centre info@eidc.ac.uk publisher University of Exeter t.r.feldpausch@exeter.ac.uk owner forest ecology GEMET - Concepts, version 4.1.3 2019-01-28 creation Human modified tropical forests Colombian Andean Altitudinal gradient Human perturbation gradient Functional traits otherRestrictions no limitations otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions If you reuse this data, you should cite: Salgado-Negret, B., Hernández-Torres, L.H., Serrano, J., López, L.G., Pennington, T., Feldpausch, T.R. (2023). Functional traits of woody plants sampled in permanent forest monitoring plots along altitudinal and forest perturbation gradients in the Colombian Andes, 2019-2022. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/0da218a8-2882-4ee7-bb2a-50a51f7f4138 textTable 1000 English utf8 biota 2019-01-01 2022-12-31 -75.55 -73.16 4.9 6.1 Comma-separated values (CSV) NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://data-package.ceh.ac.uk/data/0da218a8-2882-4ee7-bb2a-50a51f7f4138 Download the data Download a copy of this data download https://data-package.ceh.ac.uk/sd/0da218a8-2882-4ee7-bb2a-50a51f7f4138.zip Supporting information Supporting information available to assist in re-use of this dataset information dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 Forest plant trait data was obtained through direct sampling in a network of permanent forest plots of 0.5 hectares, each, located across an altitude and perturbation gradient in the Andean ecosystems of Colombia. The study collected foliar and bark data from trees, including leaf carbon, nitrogen, phosphorus, calcium, magnesium, potassium, specific leaf area, leaf dry matter content, leaf thickness, leaf area, leaf fresh mass, leaf dry mass, wood mass dry, wood density, bark thickness, and wood volume fresh. In each plot, mature trees meeting certain criteria were selected, and from each selected tree a branch with leaves and a piece of wood were collected. The leaves were randomly selected and placed on an A4 size sheet, while the piece of wood was 10 cm long and between 1 and 2 cm in diameter. Each sample was labeled with the plot code and tree number for identification. All measurements were conducted according to the methodology described by Salgado-Negret et al. (2016). The study used various techniques to calculate these parameters and ensured data quality by calculating the average for each individual considering the replicas.